Abstract

PurposeEnergy consumption of buildings is one of the major drivers of environmental impacts. Life cycle assessment (LCA) may support the assessment of burdens and benefits associated to eco-innovations aiming at reducing these environmental impacts. Energy efficiency policies however typically focus on the meso- or macro-scale, while interventions are typically taken at the micro-scale. This paper presents an approach that bridges this gap by using the results of energy simulations and LCA studies at the building level to estimate the effect of micro-scale eco-innovations on the macro-scale, i.e. the housing stock in Europe.MethodsLCA and dynamic energy simulations are integrated to accurately assess the life cycle environmental burdens and benefits of eco-innovation measures at the building level. This allows quantitatively assessing the effectiveness of these measures to lower the energy use and environmental impact of buildings. The analysis at this micro-scale focuses on 24 representative residential buildings within the EU. For the upscaling to the EU housing stock, a hybrid approach is used. The results of the micro-scale analysis are upscaled to the EU housing stock scale by adopting the eco-innovation measures to (part of) the EU building stock (bottom–up approach) and extrapolating the relative impact reduction obtained for the reference buildings to the baseline stock model. The reference buildings in the baseline stock model have been developed by European Commission-Joint Research Centre based on a statistical analysis (top–down approach) of the European housing stock. The method is used to evaluate five scenarios covering various aspects: building components (building envelope insulation), technical installations (renewable energy), user behaviour (night setback of the setpoint temperature), and a combined scenario.Results and discussionResults show that the proposed combination of bottom–up and top–down approaches allow accurately assessing the impact of eco-innovation measures at the macro-scale. The results indicate that a combination of policy measures is necessary to lower the environmental impacts of the building stock to a significative extent.ConclusionsInterventions addressing energy efficiency at building level may lead to the need of a trade-off between resource efficiency and environmental impacts. LCA integrated with dynamic energy simulation may help unveiling the potential improvements and burdens associated to eco-innovations.

Highlights

  • The building sector causes important environmental impacts in terms of resource consumption, harmful emissions, and generation of waste

  • The communication on resource efficiency opportunities in the building sector by the European Commission (EC 2014) highlights that the entire life cycle of a building must be considered in the selection of improvement options, to ensure that the environmental impacts are tackled effectively and to avoid burden shifting among life cycle stages

  • The results show that the eco-innovation scenarios mainly lead to a reduction in fossil fuel depletion, ranging from a reduction of 3% for the thermal solar system to 20% for the combined scenario

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Summary

Introduction

The building sector causes important environmental impacts in terms of resource consumption, harmful emissions, and generation of waste. The embodied impact of buildings is becoming relatively more important (Seo et al 2016; Vilches et al 2017) This is widely recognized, and recent studies increasingly focus on reducing the operational energy and the embodied impacts in parallel (Birgisdottir et al 2017; Cabeza et al 2013). In this context, the communication on resource efficiency opportunities in the building sector by the European Commission (EC 2014) highlights that the entire life cycle of a building must be considered in the selection of improvement options, to ensure that the environmental impacts are tackled effectively and to avoid burden shifting among life cycle stages. Life cycle assessment (LCA) is recognized as a valuable methodology to assess the environmental performance of eco-innovation options along the entire life cycle and to avoid burden shifting in time and among impact categories (Sala et al 2013; Yu et al 2016)

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